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Fuzzy number linear programming: a probabilistic approach (3)
H. R. Maleki,M. Mashinchi 한국전산응용수학회 2004 Journal of applied mathematics & informatics Vol.15 No.-
In the real world there are many linear programming problemswhere all decision parameters are fuzzy numbers. Several approaches existwhich use dierent ranking functions for solving these problems. Unfortu-nately when there exist alternative optimal solutions, usually with dierentfuzzy value of the objective function for these solutions, these methods cannot specify a clear approach for choosing a solution. In this paper we pro-pose a method to remove the above shortcoming in solving fuzzy numberlinear programming problems using the concept of expectation and vari-ance as ranking functions.
FUZZY NUMBER LINEAR PROGRAMMING: A PROBABILISTIC APPROACH (3)
Maleki, H.R.,Mashinchi, M. 한국전산응용수학회 2004 Journal of applied mathematics & informatics Vol.15 No.1
In the real world there are many linear programming problems where all decision parameters are fuzzy numbers. Several approaches exist which use different ranking functions for solving these problems. Unfortunately when there exist alternative optimal solutions, usually with different fuzzy value of the objective function for these solutions, these methods can not specify a clear approach for choosing a solution. In this paper we propose a method to remove the above shortcoming in solving fuzzy number linear programming problems using the concept of expectation and variance as ranking functions
A METHOD FOR SOLVING A FUZZY LINEAR PROGRAMMING
Peraei, E.Yazdany,Maleki, H.R.,Mashinchi, M. 한국전산응용수학회 2001 The Korean journal of computational & applied math Vol.8 No.2
In this paper a fuzzy linear programming problem is presented. Then using the concept of comparison of fuzzy numbers, by the aid of the Mellin transform, we introduce a method for solving this problem. AMS Mathematics Subject Classification : 90C05, 90C70
NEHI, HASSAN MISHMAST,MALEKI, HAMID REZA,MASHINCHI, MASHAALAH 한국전산응용수학회 2006 Journal of applied mathematics & informatics Vol.20 No.1
In this paper first, we find a canonical symmetrical trapezoidal(triangular) for the solution of the fuzzy linear system $A\tilde{x}=\tilde{b}$, where the elements in A and $\tilde{b}$ are crisp and arbitrary fuzzy numbers, respectively. Then, a model for fuzzy linear programming problem with fuzzy variables (FLPFV), in which, the right hand side of constraints are arbitrary numbers, and coefficients of the objective function and constraint matrix are regarded as crisp numbers, is discussed. A numerical procedure for calculating a canonical symmetrical trapezoidal representation for the solution of fuzzy linear system and the optimal solution of FLPFV, (if there exist) is proposed. Several examples illustrate these ideas.
Amin Dastanpour,Suhaimi Ibrahim,Reza Mashinchi,Ali Selamat 한국산학기술학회 2014 SmartCR Vol.4 No.6
Currently network security researchers are focusing on intrusion detection systems. The effectiveness of a Gravitational Search Algorithm in optimizing the results of an Artificial Neural Network is investigated for attack detection in an intrusion detection system. The KDD CUP ‘99 dataset is used in this study for achieving the ANN results. The results are presented before applying the GSA, and they are compared with optimal results after the GSA has been applied.